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Quality data helps governments address the impact of exclusion on societies as a whole

Throughout Latin America, race and ethnicity continue to be among the most important determinants of access to opportunity and economic advancement. Indigenous and Afro-descendant peoples in Latin America represent 40 percent of the total population—a sizeable share—yet they remain a disproportionate segment of the poorest of the poor. While a priority for social inclusion measures, they have not seen the sharp reductions in poverty experienced by the overall population and are still more likely than the general population to live in extreme poverty. In countries such as Bolivia, Guatemala, Honduras, Nicaragua, Panama, and Paraguay, for example, over 60 percent of Indigenous peoples and Afro-descendants are poor. Americas Quarterly’s Social Inclusion Index is especially useful in highlighting these discrepancies.

In Panama, for example, 90 percent of Indigenous peoples live below the poverty line and 69.5 percent live in extreme poverty, compared to just 30 percent of the non-Indigenous population. In Peru, 34 percent of Afro-descendants live below the poverty line, compared to only 23 percent of mestizos. In Brazil, per capita monthly incomes for Brazilians of European descent are more than double those of Afro-descendants. Similar poverty and income gaps can be found in countries throughout the region.

Access to Education and Employment

Indicators related to education, health, labor markets, and access to basic infrastructure depict a similar phenomenon throughout the region. Access to labor markets and economic opportunities represent a particularly sticky problem for both Afro-descendant and Indigenous populations. Despite some advances, there continue to be serious hurdles limiting Afro-descendants’ access to primary and secondary education in countries such as Colombia, Costa Rica and Panama. There are also serious concerns related to gaps in quality and access to higher education. For example, Afro-descendants obtain a university degree at half the rate of the national average in Colombia and Costa Rica, despite relative parity in primary and secondary education attainment rates.

But the gaps persist beyond education. A 2010 Ethos Institute study of 105 large businesses in Brazil found that only 5.3 percent of executives were Afro-descendants—a mere 0.5 percent were women—and that only 28 percent of those businesses had policies in place to improve Afro-descendant representation in leadership positions. Just 3 percent of the corporations studied had specific goals related to increasing the number of Afro-descendant executives. In Panama, formal sector labor market participation of Indigenous peoples is more than 30 percentage points lower than that of the non-Indigenous population. And in Colombia, a small survey of the labor market suggests that being an Afro-descendant applicant lowers the chance of receiving an initial contact for an interview by approximately 8 percent, while being white increases it by 3 percent.

Access to Services

Indigenous communities in Latin America frequently lack access to basic infrastructure services such as potable water and electricity. A recent study estimated it would take Indigenous communities between 10 and 26 years to attain the same potable water coverage rates as the non-Indigenous population, and three to 24 years to reach comparable coverage rates for access to electricity, based on the current rates of increase in their respective countries.

But we also see that financial inclusion does not guarantee quality services. For example, in Mexico, Indigenous individuals receive lower-quality health care service regardless of their personal income level. According to one report, the health care available to Indigenous peoples living in rural areas was equivalent to the quality of care available to the poorest quintile of non- Indigenous people. In other words, the poorest non Indigenous individuals have the same level of access to health care as the wealthiest Indigenous wage earners.

Afro-descendants also face important health gaps in areas such as maternal mortality and premature births throughout the Americas, regardless of income. Poorer health outcomes and evidence of discrimination in the provision of health care have been well documented. When Afro-descendants and Indigenous peoples do have access to health services, they are almost exclusively publicly provided services. There is some evidence that in places like Uruguay, whites and mestizos opt out of public health services as they become more middle class. Indigenous peoples and Afro-descendants tend not to opt out of public services and are a captive market that is more likely to be considered inferior by public health providers—creating a vicious cycle of poor quality services.

These differences in outcomes have persisted even in countries that have developed programs to overcome social, political and economic exclusion. Despite the importance of equitable opportunities for growth and development, many questions on how to effectively reduce racial and ethnic gaps remain unanswered. The full extent of this exclusion by race and ethnicity is not clearly understood because of the lack of reliable disaggregated data by race and ethnicity in the region.

Asking the Right Questions

National statistics institutes have begun to add self-identification to government surveys to respond to calls for more sophisticated measurements of race and ethnicity. The traditional reliance on language (mother tongue) to identify an individual’s ethnic origin has led, for example, to significant undercounting of the Indigenous population throughout the region. According to recent analysis of regional data, only about half (5.2 percent) of the self-identified Indigenous peoples in the region (10 percent) speak an Indigenous language. Adequate training and randomized spot checking are needed to ensure that self-identification questions are being asked consistently.

Census and household survey data are important to determine the distribution of financial resources, measure development progress and design specific development programs. As a result, disaggregated data by race has received a growing level of attention from activists and lobbyists throughout the region.

But good data is only the first step in understanding and addressing racial inequality in Latin America. The challenge for the region remains how to translate race-disaggregated data into effective policy tools. A few examples below demonstrate how improving data availability and analysis leads to better policy design.

Big Data Can Mean Big Challenges

A prime illustration is Brazil. Data on race has been collected in all national censuses since 1940 and race has been included in every annual household survey since 1987. However, the government has only recently started to harness the potential of this data as a policy tool. For example, the web-based Dataseppir and the SINAPIR data visualization policy tools were launched in 2014 by the Secretaria de Políticas de Promoção da Igualdade Racial (Secretariat for Policies to Promote Racial Equality—SEPPIR), a government agency created to help manage the Programa Brasil Quilombola (Brazil Quilombo Program), a multisector federal program designed to provide land titles and social services to the residents of thousands of Afro-Brazilian quilombo communities, which were founded by enslaved Africans in pre-abolition Brazil. The tool cross references datasets from several government ministries, including Social Development, Education, and Land Regularization, and visualizes this information in an interactive web-based environment, through (1) monitoring dashboards; (2) tools for data analysis with query-specific geographic maps; and (3) on-the-ground imaging that allows for virtual walking tours of communities. A public administrator can use the tool to identify which communities have low education levels, find the schools that are closest to a community, and even use the virtual tour feature to assess the quality of access roads to the school.

In December 2014, DataSEPPIR and the SINAPIR visualization tool were named as one of 10 finalists for the 19th Annual Innovations in Federal Public Management Prize—an award given by the prestigious Escola Nacional da Administração Pública (Brazilian National School of Public Administration—ENAP) that recognizes federal government innovations that foster efficiency in public management.

Debunking Stereotypes and Creating New Partnerships

São Paulo has developed an innovative public-private partnership through the Secretaria Municipal de Promoção da Igualdade Racial (Municipal Secretariat for the Promotion of Racial Equality—SMPIR) to improve employment and advancement opportunities for Afro-Brazilians and other vulnerable groups. During the launch of the São Paulo Diverso: Inclusive Economic Development Forum in October 2014, the municipality developed Igualdade Racial em São Paulo: Avanços e Desafios (Racial Equality in São Paulo: Progress and Challenges), an analysis of the socioeconomic conditions of Afro-Brazilian inhabitants of the city. The report highlights progress in the areas of education and violence reduction, with the goal of identifying the regions of the city with significant economic potential and sizeable Afro-descendant populations. Data from this report were used by the municipal government in the design, implementation and further evaluation of public policies focused on socioeconomic development. The data sets specifically demonstrated that the most economically active neighborhoods with large Afro-descendant populations (over 30 percent) might be eligible for new employment opportunities.

It also showed that homicide rates have fallen in the São Paulo region, particularly for Afro-descendants (from 1,650 to 394 between 2000 and 2013) and that, increasingly, Afro-descendant youth are obtaining college degrees (an increase of 273 percent from 2000 to 2010). These are all important factors to note when brokering new partnerships to promote inclusive economic development with the private sector.

CHECKLIST FOR RACIAL AND ETHNIC INCLUSION: HOW TO GET BETTER RESULTS

Public Sector

• Disaggregate data by race and ethnicity in census and household surveys.

• Increase funding to national statistics institutes to provide better national-level coverage and oversampling where relevant.

• Improve quality of data collection through training of government agencies. Engage local communities to validate the quality of national and regional data and recruit community members to support data collection exercises in remote regions.

• Keep race and ethnicity questions consistent over time to enable longitudinal comparisons across years.

• Reach out to populations that are less likely to respond or are more difficult to reach with public campaigns that raise the visibility of surveys.

• Use focus groups to pilot-test race or ethnicity questions before adding new questions to surveys.

Private Sector

• Design internal surveys to determine the racial, ethnic and gender composition of leadership and staff and consider programs to address those gaps with concrete targets.

• Consider travel support for entry-level job interviews to enable members of underrepresented groups from more remote regions to attend in-person interviews.

Oversampling to Better Understand Local Populations

In Peru, the Instituto Nacional de Estadística (National Statistics Institute–INEI) and the Ministerio de Cultura (Ministry of Culture), in collaboration with the Grupo de Análisis para el Desarrollo (Group for the Analysis of Development—GRADE), developed and implemented a nationally representative survey of Afro-descendants in 2014. The survey is a priority for the ComitéTécnico Interinstitucional sobre Estadísticas de Etnicidad (Inter-ministerial Committee on Ethnicity Studies), and is the flagship initiative of the government’s racial and ethnic inclusion committee. The survey will be used to inform future government policies in the area of race and ethnicity.

The study focuses on the 10 regions of Apurímac, Ayacucho, Callao, Ica, Lambayeque, Lima, Piura, San Martín, Tacna, and Tumbes—areas with historic and significant Afro-descendant populations. In the sample, 25 percent of all adults had obtained a degree in a professional field. Preliminary data analysis demonstrated a large discrepancy between Afro-Peruvians who witness discrimination against other Afro-Peruvians (45 percent), those who have experienced discrimination (19 percent), and those who feel that Afro-Peruvians are treated equally (49 percent). This is interesting because it demonstrates that victims of racial discrimination may not perceive that they are being discriminated against, or that racial discrimination is so stigmatized in the country that victims of racism are unwilling to report it, even in a confidential survey.

The Next Frontier: Measuring the Cost of Exclusion for Society as a Whole

Collecting quality data helps us understand and address the impact of exclusion on societies as a whole. Social inclusion agendas often focus on the consequences of exclusion on disadvantaged communities. However, it is also worthwhile to consider how the exclusion of groups impacts the larger societies in which they live. What, for example, is the economic cost to a country of allowing high levels of inequality to persist over time? How much does the exclusion of Afro-descendants and Indigenous peoples really cost Latin American societies?

Several older experiences could be worth revisiting for this analysis. One of the earliest measurements of the economic impact of exclusion was prepared in 1962 by the President’s Council of Economic Advisers in the United States. At the time, the cost of racial exclusion was estimated at about $18 billion, or 3.2 percent of U.S. Gross National Product. A 2012 study explored the economic consequences of differences in well-being across ethnic groups within 16 African countries in an attempt to study the relationship between ethnicity, inequality and development. The authors combined linguistic maps on the spatial distribution of groups in each country with satellite images of light density at night to construct Gini coefficients that reflect inequality in well-being and the provision of public goods across ethnic groups, on the assumption that more lights signify greater economic activity and better public services. The results of this study suggest that ethnic inequality is strongly negatively correlated with per capita GDP across countries. This implies that a reduction in the ethnic Gini coeffcient by 0.25 (approximately one standard deviation) is associated with a 31 percent increase in GDP per capita. Similar exercises that explore the cost of exclusion should be seriously considered in Latin America.

Quality data is essential to measuring progress toward national objectives and targeting social programs. But very few countries have consistently collected data disaggregated by race; and the data that does exist is not always suitable for making comparisons across countries, or over time. Long term, consistent and accurate data would also help Latin American countries monitor progress against international indicators.

As we have seen with regional goals, countries may be able to reach targets for the population overall but have had limited progress across racial and ethnic groups.

Governments are increasingly making decisions based on the ability to create indicators and track progress. Without quality data indicators, Afro-descendants and Indigenous peoples will remain outside of the policymaking framework. Countries that are collecting, tracking and monitoring indicators and progress will have a greater ability to promote equality and eliminate racial and ethnic gaps. Over time, it is likely that we will have even more evidence that decreasing racial and ethnic opportunity gaps is not only good for marginalized people, but also good for society as a whole.